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2019 Coronavirus disease (COVID-19) had a big impact in Italy, mainly concentrated in the northern part of the Country. All this was mainly due to similarities of this area with Wuhan in Hubei Province, according to geographical, environmental and socio-economic points of view. The basic hypothesis of this research was that the presence of atmospheric pollutants can generate stress on health conditions of the population and determine pre-conditions for the development of diseases of the respiratory system and complications related to them. In most cases the attention on environmental aspects is mainly concentrated on pollution, neglecting issues such as land management which, in some way, can contribute to reducing the impact of pollution. The reduction of land take and the decrease in the loss of ecosystem services can represent an important aspect in improving environmental quality. In order to integrate policies for environmental change and human health, the main factors analyzed in this paper can be summarized in environmental, climatic and land management. The main aim of this paper was to produce three different hazard scenarios respectively related to environmental, climatic and land management-related factors. A Spatial Analytical Hierarchy Process (AHP) method has been applied over thirteen informative layers grouped in aggregation classes of environmental, climatic and land management. The results of the health hazard maps show a disparity in the distribution of territorial responses to the pandemic in Italy. The environmental components play an extremely relevant role in the definition of the red zones of hazard, with a consequent urgent need to renew sustainable development strategies. The comparison of hazard maps related to different scenarios provides decision makers with tools to orient policy choices with a different degree of priority according to a place-based approach. In particular, the geospatial representation of risks could be a tool for legitimizing the measures chosen by decision-makers, proposing a renewed approach that highlights and takes account of the differences between the spatial contexts to be considered - Regions, Provinces, Municipalities - also in terms of climatic and environmental variables. • COVID-19 had a big impact in Italy, mainly in the northern part of the Country. • Reduction of land take and ecosystem services' loss improve environmental quality. • Environmental, climatic and land management can be leveraged for pandemic policies. • Geospatial representation of risks is a useful approach to support decision-makers. [ABSTRACT FROM AUTHOR]

This paper considers the problem of joint change detection and identification assuming multiple composite post-change hypotheses. We propose a multihypothesis changepoint detection-identification procedure that controls the probabilities of false alarm and wrong identification. We show that the proposed procedure is asymptotically minimax and pointwise optimal, minimizing moments of the detection delay as probabilities of false alarm and wrong identification approach zero. The asymptotic optimality properties hold for general stochastic models with dependent and nonidentically distributed observations. We illustrate general results for detection-identification of changes in multistream Markov ergodic processes. We consider several examples, including an application to rapid detection-identification of COVID-19 in Italy. Our proposed sequential algorithm allows much faster detection of COVID-19 than standard methods. [ABSTRACT FROM AUTHOR]